LEADER 05314nam 2200649Ia 450 001 996213204703316 005 20230617035031.0 010 $a9786610213399 010 $a1-280-21339-6 010 $a1-4443-0535-2 010 $a1-4051-4814-4 035 $a(CKB)1000000000351756 035 $a(EBL)238452 035 $a(OCoLC)85810803 035 $a(SSID)ssj0000251152 035 $a(PQKBManifestationID)11216564 035 $a(PQKBTitleCode)TC0000251152 035 $a(PQKBWorkID)10245253 035 $a(PQKB)10369051 035 $a(MiAaPQ)EBC238452 035 $a(EXLCZ)991000000000351756 100 $a20050921d2005 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aStatistical treatment of analytical data$b[electronic resource] /$fZeev B. Alfassi, Zvi Boger, Yigal Ronen 210 $aOxford $cBlackwell Science$d2005 215 $a1 online resource (272 p.) 300 $aDescription based upon print version of record. 311 $a0-8493-2436-X 311 $a0-632-05367-4 320 $aIncludes bibliographical references and index. 327 $aStatistical Treatment of Analytical Data; Contents; Preface; 1 Introduction; 1.1 Statistics and quality assurance, control and assessment; 1.2 References; 2 Statistical measures of experimental data; 2.1 Mean and standard deviation; 2.2 Graphical distributions of the data - bar charts or histograms; 2.3 Propagation of errors (uncertainties); 2.4 References; 3 Distribution functions; 3.1 Confidence limit of the mean; 3.2 Measurements and distribution functions; 3.3 Mathematical presentation of distribution and; 3.4 Continuous distribution functions; 3.5 Discrete distribution functions 327 $a3.6 References4 Confidence limits of the mean; 4.1 Confidence limits; 4.2 The Central Limit Theorem - the distribution of means; 4.3 Confidence limit of the mean; 4.4 Confidence limits of the mean of small samples; 4.5 Choosing the sample size; 5 Significance test; 5.1 Introduction; 5.2 Comparison of an experimental mean with an expected; 5.3 Comparison of two samples; 5.4 Paired t-test; 5.5 Comparing two variances - the F-test; 5.6 Comparison of several means; 5.7 The chi-squared (x2) test; 5.8 Testing for normal distribution - probability paper; 5.9 Non-parametric tests; 5.10 References 327 $a6 Outliers6.1 Introduction; 6.2 Dixon's Q-test; 6.3 The rule of huge error; 6.4 Grubbs test for outliers; 6.5 Youden test for outlying laboratories; 6.6 References; 7 Instrumental calibration - regression analysis; 7.1 Errors in instrumental analysis vs. classical 'wet chemistry' methods; 7.2 Standards for calibration curves; 7.3 Derivation of an equation for calibration curves; 7.4 Least squares as a maximum likelihood estimator; 7.5 Tests for linearity; 7.6 Calculation of the concentration; 7.7 Weighted least squares linear regression; 7.8 Polynomial calibration equations 327 $a7.9 Linearization of calibration curves in nuclear measurements7.10 Non-linear curve fitting; 7.11 Fitting straight-line data with errors in both coordinates; 7.12 Limit of detection; 7.13 References; 8 Identification of analyte by multi-measurement analysis; 8.1 References; 9 Smoothing of spectra signals; 9.1 Introduction; 9.2 Smoothing of spectrum signals; 9.3 Savitzky and Golay method (SG method); 9.4 Studies in noise reduction; 9.5 Extension of SG method; 9.6 References; 10 Peak search and peak integration; 10.1 A statistical method; 10.2 First derivative method 327 $a10.3 Second derivative method10.4 Computer - visual separation of peaks; 10.5 Selection of the fitting interval and integration; 10.6 References; 11 Fourier Transform methods; 11.1 Fourier Transform methods in spectroscopy; 11.2 Mathematics of Fourier Transforms; 11.3 Discrete Fourier Transforms; 11.4 Fast Fourier Transforms (FFT); 11.5 References; 12 General and specific issues in uncertainty analysis; 12.1 Introduction; 12.2 The uncertainty era; 12.3 Uncertainties and the laws of nature; 12.4 The creation of the universe and the law of energy and mass 327 $a12.5 Statistical and systematic uncertainties 330 $aStatistical techniques have assumed an integral role in both the interpretation and quality assessment of analytical results. In this book the range of statistical methods available for such tasks are described in detail, with the advantages and disadvantages of each technique clarified by use of examples. With a focus on the essential practical application of these techniques the book also includes sufficient theory to facilitate understanding of the statistical principles involved. 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